模糊神经网络技术在纳税评估中的应用研究

【作者】 鲁倩；

【导师】 魏长江； 杜长河；

【作者基本信息】 青岛大学 ， 软件工程， 2006， 硕士

【摘要】 我国税务系统在实施以综合征管、增值税专用发票稽核协查、防伪税控、出口退税、多元化电子申报纳税和行政管理办公自动化等系统为核心的信息化建设中，相继实现了省级以上的数据集中模式，初步形成了多个应用系统共享一个网络的格局。这些系统的运行产生了大量业务数据，如何将这些数据进行整合、分析和挖掘，以支持目前和今后税收的科学管理与决策，成为当前税务信息化的重要工作。因此，数据挖掘技术在税收征管领域的应用是税务部门提高执法、行政能力的必然选择。在以往的税收纳税评估工作中，常常由于信息量不足得不到充分分析或信息过多造成冗余。针对这些问题，本文在对模糊理论和神经网络技术的基本原理及两者在数据挖掘中的优点和缺点进行了研究和分析的基础上，通过建立数学模型，将模糊规则与神经网络相结合，实现一种新的推理方法。本文通过对几种算法的分析比较，提出随机学习自动机算法在应用中具有的优势，并通过此算法进行模型设计得出仿真结果。该方法对提高基础数据的分析和利用水平，发现数据的价值具有较好的应用效果，在此基础上讨论在纳税评估应用中如何将纳税人的情况真实、准确、合法地进行审核、分析，并依法及时进行评定处理，为税务管理部门决策提供帮助。更多还原

【Abstract】 With the rapid development in the building of information in taxation bureau, a great number of data have been generated from each respective application system, such as CTAIS, OA, etc. However, as these data are placed dispersedly, meaning differentiated, it is hard to turn these data into useful information. All of these data should be integrated, transformed, cleaned, extracted and loaded to data warehouse that help to change the data valuable. And organizations need the suitable knowledge to operate their business.In order to serve managers more conveniently to make up their decisions and to solve problems in ratepaying evaluation in the past, this paper presents an approach, that is, making use of fuzzy neural network in data mining. This paper introduces some basic theories, models and methods of fuzzy logic, neural network, Analyses the advantage and shortage in data mining, and explains the necessary of combining the two methods. The method puts forward a new way to improve the value in using of data. By comparing and analysing several methods, this paper brings up the advantage of stochastic learning automation. According to this method, emulation result has worked out. The result shows that it has better effect in finding out data value. Based on this method, this paper discusses how to audit the information of taxpayers accurately. It helps the administration of taxation to make decisions.更多还原